Subjective perception of objects depends on the interaction between the validity of context-based expectations and...

Predictive coding theories of visual perception assume that expectations based on prior knowledge modulate the processing of information. However, the underlying mechanisms remain debated. Some accounts propose that expectations enhance the perception of expected relative to unexpected stimuli while others assume the opposite. Recently, the opposing process theory suggested that enhanced perception of expected vs. unexpected stimuli may occur alternatively depending upon the reliability of the visual signal. When the signal is noisy, perception would be biassed toward what is expected since anything else may be too noisy to be resolved. When the signal is unambiguous, perception would be biassed toward what diverges from expectations and is more informative. Our study tested this hypothesis, using a perceptual matching task to investigate the influence of expectations on the perceived sharpness of objects in context. Participants saw two blurred images depicting the same object and had to adjust the blur level of one object to match the blur level of the other one. We manipulated the validity of expectations about objects by varying their scene context (congruent or incongruent context leading to valid or invalid expectations about the object). We also manipulated the reliability of the visual signal by varying the initial blur level of object pairs. Results showed that expectations validity differentially affected the perception of objects depending on signal reliability. Perception of validly expected objects was enhanced (sharpened) relative to unexpected objects when visual inputs were unreliable while this effect reversed to the benefit of unexpected objects when the signal was more reliable.